LDLMIn construction

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Size
306M trained
Published
Meshchaninov et al. · May 2026
Line
Diffusion language model
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Architecture
Source

LDLM @ e18c42a, not yet public · arXiv:2605.07933v1 · OpenWebText · 1024 · checkpoint, tokenizer and saved statistics not verifiedHow to read

TrainingGeneration

Detokenizer

×

no parameters

Turn each sequence of token IDs back into text.

in
II [B batch, T positions]
Explanation

truncate_eos is false in this configuration: the whole sequence is decoded, special tokens included.

Sources3

Direct evidence

Generation: the sampled latents pass the latent decoder and the token decoder, each position takes the token of the largest logit, and the tokens are decoded to text, special tokens kept unless truncation is on.

The implementation, pinned at revision e18c42acdfb7, not yet public

Direct evidence

Generation: sequences are not truncated at the end token, and the trained adaptive time grid is used.

The implementation, pinned at revision e18c42acdfb7, not yet public

Direct evidence

The tokenizer is loaded by name, set up, and gains a `<mask>` token when it has none; the vocabulary size is its length.

The implementation, pinned at revision e18c42acdfb7, not yet public